A Hilbert Space Approach to Variance Reduction

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Authors
Szechtman, Roberto
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Date of Issue
2006
Date
2006
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Abstract
In this chapter we explain variance reduction techniques from the Hilbert space standpoint, in the terminating simulation context. We use projection ideas to explain how variance is reduced, and to link different variance reduction techniques. Our focus is on the methods of control variates, conditional Monte Carlo, weighted Monte Carlo, stratification, and Latin hypercube sampling.
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Book Chapter
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Elsevier Handbooks in Operations Research and Management Science: Simulation, pp 259-289.
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Operations Research (OR)
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2006. A Hilbert Space Approach to Variance Reduction. Elsevier Handbooks in Operations Research and Management Science: Simulation (edited by S.G. Henderson and B.L. Nelson), Elsevier, Amsterdam, pp 259-289.
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defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
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